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Remote sensing

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Articles 91 - 120 of 707

Full-Text Articles in Physical Sciences and Mathematics

Machine Learning Methods For Quantification Of Glacier Variations Through Satellite Imagery, Robert D. Breininger Dec 2024

Machine Learning Methods For Quantification Of Glacier Variations Through Satellite Imagery, Robert D. Breininger

Theses and Dissertations

Glaciers around the world have experienced a trend of recession within the past century. Quantification of glacier variations using satellite imagery is of great interest due to the importance of glaciers as freshwater resources and as indicators of climate change. The potential methods to quantify glacier variations with increasing complexity include detecting the terminus location, quantifying the glacier surface area, and measuring glacier volume. Although there are methods in literature designed purposefully for glacier area segmentation that have achieved acceptable results, they are often localized to the region where their training data were acquired and further rely on training sets …

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Landslide Inventory And Unstable Slope Monitoring Along Highways In Eastern Tennessee, Robert Mcsweeney Dec 2024

Landslide Inventory And Unstable Slope Monitoring Along Highways In Eastern Tennessee, Robert Mcsweeney

Electronic Theses and Dissertations

This research introduces an unstable slope management program (USMP) for Tennessee based on federal slope management standards, along with improved methods for landslide monitoring with unmanned aerial systems (UAS) lidar and photogrammetry. In mountainous regions, monitoring slope hazards is a critical function of transportation management. A mobile field assessment form created with Survey123 was used to collect 22 unstable slope ratings in eastern Tennessee. Location points were appended with photographs, notes, and site information. Landslide scores ranged from 325 (Fair) to 1005 (Poor). UAS monitoring of a slow-moving soil landslide along I-40 near Rockwood, TN, produced high-resolution lidar and photogrammetry …

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On Spatiotemporal Trends In Meter-Scale Gris Surface Roughness And The Development Of An On-Ice Laser Distance Meter, Jamie C. Good Nov 2024

On Spatiotemporal Trends In Meter-Scale Gris Surface Roughness And The Development Of An On-Ice Laser Distance Meter, Jamie C. Good

Dartmouth College Master’s Theses

Surface roughness is a critical component of the energy and mass balance of the Greenland Ice Sheet (GrIS). However, roughness is often oversimplified in predictive models due to its inherent scale dependency. Accurate quantification of roughness, including its recent changes and driving factors, is critically important for understanding and predicting GrIS surface dynamics. Using multi- and single-scale methods of roughness analysis, I assess spatiotemporal trends in GrIS meter-scale surface roughness from 2009 to 2019 with Operation IceBridge’s Airborne Topographic Mapper ILATM2 product. Additionally, with data from on-ice automated weather stations, I employ machine learning techniques to identify primary climatic controls …

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Sward Production Estimated By Spectral Reflectance, G Nagy, V Zilinyi Aug 2024

Sward Production Estimated By Spectral Reflectance, G Nagy, V Zilinyi

IGC Proceedings (1977-2023)

A non-destructive spectral reflectance method was used for the measurement of aerial biomass yields of different grasslands. Vegetation indices {VI) were calculated from the green, red and near-infrared light reflectance. These indices were compared with actual grass yields cut just after the reflectance measurement. The correlation coefficient between actual yields and VI was significant (r=0.969,n=24). This non-destructive technique is therefore a reliable tool for the estimation of standing biomass of grasslands.

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Application Of Neural Networks To The Extraction Of Various Types Of Grasslands In Japan Using Landsat Thematic Mapper Data, Mikinori Tsuiki, Shigeo Takahashi, Toshiki Oku Aug 2024

Application Of Neural Networks To The Extraction Of Various Types Of Grasslands In Japan Using Landsat Thematic Mapper Data, Mikinori Tsuiki, Shigeo Takahashi, Toshiki Oku

IGC Proceedings (1977-2023)

A neural network was applied to the extraction of various types of grasslands using Landsat Thematic Mapper (TM) data. Training fields contained 12 classes (water, paddy field, farmland, sands and rocks, urban area, coniferous forest, deciduous forest, golf course, Sasa­type grassland, Miscanthus type grassland, meadow before culling and meadow after cutting). Classification performance using the neural network was 99.4%, which was 2.4% higher than that obtained using the maximum likelihood method. For all types of grasslands, classification performance was 99.8%. The results of the classification area obtained using the neural network and the maximum likelihood method resembled each other. …

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Key Largo Mangrove Population Monitoring: A Remote Sensing Analysis And Classification Methodology Review, David Lackajs Aug 2024

Key Largo Mangrove Population Monitoring: A Remote Sensing Analysis And Classification Methodology Review, David Lackajs

Geography and the Environment: Graduate Student Capstones

Mangrove forests are some of the world's most bio-diverse habitats, providing essential services to the surrounding coasts. Removal of these habitats has a devastating impact on the ecosystems within them. The Florida Keys are some of the last areas in the United States with extensive mangrove populations. One specific area, John Pennekamp Coral Reef State Park in Key Largo, has been under state protection since 1959. For that reason, mangrove forest habitats there are less fragmented. This study uses remotely sensed imagery to quantify and analyze mangrove populations in this area using two methods: sub-pixel analysis and supervised classification. The …

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Grassland Investigation And Mapping Using Remote Sensing In Northern China, Liu Fuyuan, Li Znegyuan, Han Jinaguoguez, Xia Jingxin Aug 2024

Grassland Investigation And Mapping Using Remote Sensing In Northern China, Liu Fuyuan, Li Znegyuan, Han Jinaguoguez, Xia Jingxin

IGC Proceedings (1977-2023)

A large area of grassland in north China is an important resource for animal production, The grassland vegetations of north China were investigated and mapped by means of remote sensing from 1986 to 1990, We adopted various multiple information and multitime phase satellite images which were taken to allow optical and computer processing for complicated cases and difficult areas of grassland classification, The grasslands were divided into 8 different types and 50 groups according to surface features of Landsat images, ecological environment and vegetation analysis, The warm shrub and herbosa grassland, which ls distributed mainly in the rocky mountainous regions, …

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Mapping Urban Tree Canopy Using Publicly Available Satellite Data, Rosemary Mcguinness Aug 2024

Mapping Urban Tree Canopy Using Publicly Available Satellite Data, Rosemary Mcguinness

Theses and Dissertations

This project addresses the need for accessible, cost-effective tools for quantifying spatial and temporal changes in tree canopy cover in urban areas. Urban tree canopy provides a wide range of ecosystem services, including lowering air temperatures, reducing pollution, and mitigating stormwater runoff. Cities around the world have placed the expansion of their urban forests at the center of their sustainability goals. Consistent and timely data on urban tree canopy is essential for urban greening initiatives to succeed. Existing methods of accessing information about urban tree canopy are highly technical, costly, and labor-intensive, while the freely available source of tree canopy …

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Applications Of Artificial Intelligence On Drought Impact Monitoring And Assessment, Beichen Zhang Aug 2024

Applications Of Artificial Intelligence On Drought Impact Monitoring And Assessment, Beichen Zhang

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Drought, a prevalent and consequential natural disaster, poses widespread, indirect challenges across environmental and societal dimensions. Despite considerable focus on monitoring meteorological and hydrological drought and studying their characteristics, there is a gap in assessing its multifaceted impacts, especially on societal sectors. The dissertation comprises three research essays utilizing artificial intelligence to quantitatively study multi-dimensional drought impacts. The first essay leveraged deep learning and natural language processing to predict multi-dimensional drought impacts from textual datasets, including social media, news media, and citizen scientist reports. The findings demonstrate superior performance over traditional methods and unveil the spatial and temporal heterogeneity of …

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Remotely Sensed Early Warning Of Algal Blooms In An Eastern Nebraska Reservoir: A Comparison Of Temporal And Spatial Indicators, Mercy Kipenda Aug 2024

Remotely Sensed Early Warning Of Algal Blooms In An Eastern Nebraska Reservoir: A Comparison Of Temporal And Spatial Indicators, Mercy Kipenda

School of Natural Resources: Dissertations, Theses, and Student Research

Cyanobacterial harmful algal blooms (CyanoHABs) detrimentally affect human, animal, and ecosystem health. Remotely sensed early warning systems for cyanoHABs in inland lakes could contribute to more proactive water quality monitoring and help mitigate negative impacts. Advances in freely available remote sensing imagery, with finer spatial, temporal, and spectral resolutions, present new opportunities for the development and comparative analysis of methods to detect sudden deterioration in lake water quality. In this thesis, I compared and tested for temporal and spatial early warning signals of cyanoHABs in field-based and remotely sensed datasets from 2019 to 2023 in Pawnee Lake in southeast Nebraska, …

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Fishing Vessel Detection In Exclusive Economic Zones From Low Earth Orbit Satellites With Power And Computational Constraints, Kyler E. Nelson Aug 2024

Fishing Vessel Detection In Exclusive Economic Zones From Low Earth Orbit Satellites With Power And Computational Constraints, Kyler E. Nelson

All Graduate Theses and Dissertations, Fall 2023 to Present

Illegal fishing activities pose a significant threat to the sustainability of marine ecosystems and the economies and societies which rely on them. Detection of fishing vessels engaging in illegal activity is difficult, as many ships engaging in such activity actively avoid detection through radio systems used for maritime traffic monitoring. Satellite imagery provides a promising means for detecting fishing vessels, though designing an effective system is difficult due to limited availability of labeled image datasets of fishing vessels. This research proposes a system to detect illegal fishing activity through the use of a low-power ship detection satellite and proposes a …

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Deep Space Observations Of Conditionally Averaged Global Reflectance Patterns, Alexander Kostinski, Alexander Marshak, Tamás Várnai Jul 2024

Deep Space Observations Of Conditionally Averaged Global Reflectance Patterns, Alexander Kostinski, Alexander Marshak, Tamás Várnai

Michigan Tech Publications

The Deep Space Climate Observatory (DSCOVR) spacecraft drifts about the Lagrangian point ≈ 1.4 − 1.6 × 106 km from Earth, where its Earth Polychromatic Imaging Camera (EPIC) observes the entire sunlit face of Earth every 1–2 h. In an attempt to detect “signals,” i.e., longer-term changes and semi-permanent features such as the ever-present ocean glitter, while suppressing geographic “noise,” in this study, we introduce temporally and conditionally averaged reflectance images, performed on a fixed grid of pixels and uniquely suited to the DSCOVR/EPIC observational circumstances. The resulting images (maps), averaged in time over months and conditioned on surface/cover type …

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A Comparative Analysis Of Openet For Evaluating Evapotranspiration In California Almond Orchards, Kyle Knipper, Martha Anderson, Nicholas Bambach, Forrest Melton, Zac Ellis, Yun Yang, John Volk, Andrew J. Mcelrone, William Kustas, Matthew Roby, Will Carrara, Sebastian Castro, Ayse Kilic, Joshua B. Fisher, Anderson Ruhoff, Gabriel B. Senay, Charles Morton, Sebastian Saa, Richard G. Allen Jul 2024

A Comparative Analysis Of Openet For Evaluating Evapotranspiration In California Almond Orchards, Kyle Knipper, Martha Anderson, Nicholas Bambach, Forrest Melton, Zac Ellis, Yun Yang, John Volk, Andrew J. Mcelrone, William Kustas, Matthew Roby, Will Carrara, Sebastian Castro, Ayse Kilic, Joshua B. Fisher, Anderson Ruhoff, Gabriel B. Senay, Charles Morton, Sebastian Saa, Richard G. Allen

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The almond industry in California faces water management challenges that are being exacerbated by droughts, climate change, and groundwater sustainability legislation. The Tree-crop Remote sensing of Evapotranspiration eXperiment (T-REX) aims to explore opportunities to improve precision irrigation management for woody perennial cropping systems. Almond orchards in the California Central Valley were equipped with eddy covariance flux measurements to evaluate satellite remote sensing-based evapotranspiration (RSET) models. OpenET provides high-resolution (30-m spatial and daily temporal) RSET data, synthesizing decades of research for practical water management. This study provides an evaluation of OpenET performance at six almond sites covering a large range in …

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Integrating Satellite Images And Species-Based Vegetation Maps To Manage Native Grasslands, M Hall-Beyer, Q.H. J. Gwyn Jun 2024

Integrating Satellite Images And Species-Based Vegetation Maps To Manage Native Grasslands, M Hall-Beyer, Q.H. J. Gwyn

IGC Proceedings (1977-2023)

Satellite image mapping of grasslands is problematic when species diversity occurs at a sub-pixel scale. We propose a method, called melody classification, to map ground cover units that group several spectral classes (colours). Melodies are defined as the normalized expected frequencies of each class within the ground cover unit. Starting from an unsupervised classification, an image is created showing the probability of finding each spectral class in the vicinity of each pixel. Each pixel is classified by comparing the melody in its neighbourhood with that of each ground cover unit. Accuracies are greatly enhanced over those of supervised classification. Melody …

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The Ecosystem As Super-Organ/Ism, Revisited: Scaling Hydraulics To Forests Under Climate Change, Jeffrey D. Wood, Matteo Detto, Marvin Browne, Nathan J.B. Kraft, Alexandra G. Konings, Joshua B. Fisher, Gregory R. Quetin, Anna T. Trugman, Troy S. Magney, Camila D. Medeiros, Nidhi Vinod, Thomas N. Buckley, Lawren Sack Jun 2024

The Ecosystem As Super-Organ/Ism, Revisited: Scaling Hydraulics To Forests Under Climate Change, Jeffrey D. Wood, Matteo Detto, Marvin Browne, Nathan J.B. Kraft, Alexandra G. Konings, Joshua B. Fisher, Gregory R. Quetin, Anna T. Trugman, Troy S. Magney, Camila D. Medeiros, Nidhi Vinod, Thomas N. Buckley, Lawren Sack

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Classic debates in community ecology focused on the complexities of considering an ecosystem as a super-organ or organism. New consideration of such perspectives could clarify mechanisms underlying the dynamics of forest carbon dioxide (CO2) uptake and water vapor loss, important for predicting and managing the future of Earth's ecosystems and climate system. Here, we provide a rubric for considering ecosystem traits as aggregated, systemic, or emergent, i.e., representing the ecosystem as an aggregate of its individuals, or as a metaphorical or literal super-organ or organism. We review recent approaches to scaling-up plant water relations (hydraulics) concepts developed for …

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From Pixels To Plants: Remote Sensing Of California Invasive Plants, Kenneth Rangel May 2024

From Pixels To Plants: Remote Sensing Of California Invasive Plants, Kenneth Rangel

Master's Projects and Capstones

Invasive plants cause significant impacts to ecosystems, the economy, and human health. California has experienced significant plant invasions and is well suited to future invasion because of its Mediterranean climate and human disturbance. Eradication or control of invasive plant species requires a detailed understanding of their spatial distribution, which typically involves on the ground surveys that can be expensive or inconsistent. Remote sensing offers a potential alternative or supplement to in-person invasive plant mapping. This study performed a comparative analysis of 41 remote sensing studies that mapped the distribution of California invasive plants. I found that while high spectral resolution …

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Agroecology And Soil Stewardship: Values And Techniques Of Smallholder Farmers In Bernalillo County, Stephanie Olivas May 2024

Agroecology And Soil Stewardship: Values And Techniques Of Smallholder Farmers In Bernalillo County, Stephanie Olivas

Geography ETDs

Agrarian movements around the world use agroecology to build sovereignty and steward dynamic ecosystems. Research has shown that agroecological farmers steward more resilient crops, more resilient soil biomes, and greater biodiversity than conventional agriculture. GIS and remote sensing offer many tools to detect the impacts of these farmers on the environment, but it is less clear how such technologies fit into agroecological goals. This study asks: what values, experiences and knowledge do smallholder producers in Bernalillo County embody in their soil stewardship practices? Also, what experience or knowledge do smallholder producers in Bernalillo County have about remote sensing, and would …

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Triggers Of Rapid Change In Glacier Dynamics, Jukes Liu May 2024

Triggers Of Rapid Change In Glacier Dynamics, Jukes Liu

Boise State University Theses and Dissertations

The loss of land ice has become the greatest contributor to global mean sea level rise since 2006 (Oppenheimer et al., 2019). Glaciers have contributed ∼20% to global sea level rise over the last ∼2 decades (Oppenheimer et al., 2019; Hugonnet et al., 2021), while the ice sheets have contributed 33% (Oppenheimer et al., 2019). For the outlet glaciers and ice streams that drain the Greenland and Antarctic ice sheets, changes to their dynamics (flow speed, thickness, and length) dominate their present and future mass loss (King et al., 2020; Diener et al., 2021). One of the main limitations in …

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Microwave Emission Model Parameter Tuning For Surface Soil Moisture Retrieval Using Uav-Mounted Dual Polarization L-Band Radiometer, Santiago Hoyos Echeverri May 2024

Microwave Emission Model Parameter Tuning For Surface Soil Moisture Retrieval Using Uav-Mounted Dual Polarization L-Band Radiometer, Santiago Hoyos Echeverri

Open Access Theses & Dissertations

Surface soil moisture retrieval from L-band brightness temperature has been developed for the past decades due to multiple beneficial characteristics of 1-2 GHz frequency bands for remote sensing of the environment. Numerous microwave emission models have been proposed for tower and satellite-based operations with successful retrieval of surface soil moisture and vegetation water content. As a result of the development of cost-effective and low-mass microwave L-band radiometers such as the Portable L-band Radiometer (PoLRa), surface soil moisture surveying traditionally developed by satellite missions SMOS and SMAP can now be developed at local scales, bringing these operations to commercial small unmanned …

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Classification Of Remote Sensing Image Data Using Rsscn-7 Dataset, Satya Priya Challa May 2024

Classification Of Remote Sensing Image Data Using Rsscn-7 Dataset, Satya Priya Challa

Electronic Theses, Projects, and Dissertations

A novel technique for remote sensing image scene classification is employed using the Compact Vision Transformer (CVT) architecture. This model strengthens the power of deep learning and self-attention algorithms to significantly intensify the accuracy and efficiency of scene classification in remote sensing imagery. Through extensive training and evaluation of the RSSCNN7 dataset, our CVT-based model has achieved an impressive accuracy rate of 87.46% on the original dataset. This remarkable result underscores the prospect of CVT models in the domain of remote sensing and underscores their applicability in real-world scenarios. Our report furnishes an elaborate account of the model's architecture, training …

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Nowcasting Heavy Rainfall With Convolutional Long Short-Term Memory Networks: A Pixelwise Modeling Approach, Yi Victor Wang, Seung Hee Kim, Geunsu Lyu, Choeng-Lyong Lee, Soorok Ryu, Gyuwon Lee, Ki-Hong Min, Menas C. Kafatos Apr 2024

Nowcasting Heavy Rainfall With Convolutional Long Short-Term Memory Networks: A Pixelwise Modeling Approach, Yi Victor Wang, Seung Hee Kim, Geunsu Lyu, Choeng-Lyong Lee, Soorok Ryu, Gyuwon Lee, Ki-Hong Min, Menas C. Kafatos

Institute for ECHO Articles and Research

The recent decades have seen an increasing academic interest in leveraging machine learning approaches to nowcast, or forecast in a highly short-term manner, precipitation at a high resolution, given the limitations of the traditional numerical weather prediction models on this task. To capture the spatiotemporal associations of data on input variables, a deep learning (DL) architecture with the combination of a convolutional neural network and a recurrent neural network can be an ideal design for nowcasting rainfall. In this study, a long short-term memory (LSTM) modeling structure is proposed with convolutional operations on input variables. To resolve the issue of …

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Remote Sensing Techniques To Determine Volcanic Gas Components And Fluxes: Application For Lascar, Chile And Fagradalsfjall, Iceland Volcanos., Felipe S. Rojas Vilches Apr 2024

Remote Sensing Techniques To Determine Volcanic Gas Components And Fluxes: Application For Lascar, Chile And Fagradalsfjall, Iceland Volcanos., Felipe S. Rojas Vilches

Earth and Planetary Sciences ETDs

Volcanic plumes allow us to understand different aspects of a volcanic system including magma movements, dynamics, mass transfer, overall gas emissions to the atmosphere, and many processes that impact human life. However, the H₂O gas is poorly constrained due to the intrinsic difficulties of this gas, with high background values and easily dispersed/integrated into the background. In this work we study the gas emissions from Lascar volcano, and Fagradalsfjall volcano, in Chile and Iceland, respectively, using a combination of different ground-based remote sensing techniques and in situ plume measurements, we measure H₂O, SO₂, CO₂, CO, and H₂S from longer and …

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Automated Glacier Classification In High Mountain Asia Using Machine Learning And A Random Forest Classifier, Victoria Elizabeth Halvorson Apr 2024

Automated Glacier Classification In High Mountain Asia Using Machine Learning And A Random Forest Classifier, Victoria Elizabeth Halvorson

Dartmouth College Master’s Theses

High Mountain Asia (HMA) is home to the largest mass of glaciers and ice outside the north and south polar regions. HMA glaciers are projected to experience accelerated mass loss from higher greenhouse gas emissions through the end of the century. Many studies of glacier mass balance and mass loss in HMA obtain glacier area from the Randolph Glacier Inventory (RGI). However, the RGI is designed to show glacier area across the world that is accurate to the year 2000 and, as a result, is not an accurate representation of the current state of glacier area in HMA. Additionally, glacier …

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Relocating Lubra Village And Visualizing Himalayan Flood Damages With Remote Sensing, Ronan Wallace, Yungdrung Tsewang Gurung, Ryan Kastner Feb 2024

Relocating Lubra Village And Visualizing Himalayan Flood Damages With Remote Sensing, Ronan Wallace, Yungdrung Tsewang Gurung, Ryan Kastner

Journal of Critical Global Issues

As weather patterns change worldwide, isolated communities impacted by climate change go unnoticed and we need community-driven solutions. In Himalayan Mustang, Nepal, indigenous Lubra Village faces threats of increasing flash flooding. After every flood, residual muddy sediment hardens across the riverbed like concrete, causing the riverbed elevation to rise. As elevation increases, sediment encroaches on Lubra’s agricultural fields and homes, magnifying flood vulnerability. In the last monsoon season alone, the Lubra community witnessed floods swallowing several agricultural fields and damaging two homes. One solution considers relocating the village to a new location entirely. However, relocation poses a challenging task, as …

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Predicting Forage Provision Of Grasslands Across Climate Zones By Hyperspectral Measurements, F. A. Männer, J. Muro, J. Ferner, S. Schmidtlein, A. Linstädter Feb 2024

Predicting Forage Provision Of Grasslands Across Climate Zones By Hyperspectral Measurements, F. A. Männer, J. Muro, J. Ferner, S. Schmidtlein, A. Linstädter

IGC Proceedings (1977-2023)

The potential of grasslands’ fodder production is a crucial management measure, while its quantification is still laborious and costly. Remote sensing technologies, such as hyperspectral field measurements, enable fast and non-destructive estimation. However, such methods are still limited in transferability to other locations or climatic conditions. With this study, we aim to predict forage nutritive value, quantity, and energy yield from hyperspectral canopy reflections of grasslands across three climate zones. We took hyperspectral measurements with a field spectrometer from grassland canopies in temperate, tropical and semi-arid grasslands, and analyzed corresponding biomass samples for their quantity (BM), metabolizable energy content (ME) …

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Drone And Digital Camera Imagery Estimate C3 And C4 Grass Ratios In Pastures, J. A. Bush, C. D. Teutsch, S. R. Smith, J. C. Henning Feb 2024

Drone And Digital Camera Imagery Estimate C3 And C4 Grass Ratios In Pastures, J. A. Bush, C. D. Teutsch, S. R. Smith, J. C. Henning

IGC Proceedings (1977-2023)

The following study investigates the accuracy and practicality of exploiting the color dichotomy present between C3 and C4 grass species to estimate their respective proportions from drone or camera captured imagery. Understanding the proportions of C3 and C4 grasses in pastures is vital to sound decision making for livestock production. The ability to monitor these proportions remotely will also allow for large scale monitoring as well as detection of changes in botanical composition over time and in response to weather events, management, or climate change. A free green canopy cover (GCC) analyzing software, Canopeo, was used to quantify green plants …

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Prospects For Improving Alfalfa Yield Using Genomic- And Phenomic-Based Breeding, M. W. Francis, D. Pap, A. Krill-Brown, E. C. Brummer Jan 2024

Prospects For Improving Alfalfa Yield Using Genomic- And Phenomic-Based Breeding, M. W. Francis, D. Pap, A. Krill-Brown, E. C. Brummer

IGC Proceedings (1977-2023)

Alfalfa (Medicago sativa L.) is a perennial outcrossing legume that is cultivated as an important forage crop in many parts of the world. Yield is the most important trait for profitable alfalfa production, yet over the last 30 years yield improvement in California has stagnated. Current breeding methods focus on recurrent phenotypic selection; however, alternatives incorporating genomic- and phenomic-based information may enhance genetic gain and help to address the lack of yield improvement. Here we attempt to increase the yield potential of alfalfa using genomic selection (GS) in combination with high throughput phenotyping (HTP). A total of 193 families …

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A Comparative Analysis Of Openet For Evaluating Evapotranspiration In California Almond Orchards, K. Knipper, M. Anderson, N. Bambach, F. Melton, Z. Ellis, Y. Yang, J. Volk, A. J. Mcelrone, W. Kustas, M. Roby, W. Carrara, S. Castro, Ayse Kilic Jan 2024

A Comparative Analysis Of Openet For Evaluating Evapotranspiration In California Almond Orchards, K. Knipper, M. Anderson, N. Bambach, F. Melton, Z. Ellis, Y. Yang, J. Volk, A. J. Mcelrone, W. Kustas, M. Roby, W. Carrara, S. Castro, Ayse Kilic

School of Natural Resources: Faculty Publications

No abstract provided.

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Planet’S Biomass Proxy For Monitoring Aboveground Agricultural Biomass And Estimating Crop Yield, T. E. Franz Jan 2024

Planet’S Biomass Proxy For Monitoring Aboveground Agricultural Biomass And Estimating Crop Yield, T. E. Franz

School of Natural Resources: Faculty Publications

No abstract provided.

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Mesmerizing Moon Mysteries: Unraveling The Compositions Of Irregular Mare Patches (Imps) Using Remote Observations, Nicholas G. Piskurich Jan 2024

Mesmerizing Moon Mysteries: Unraveling The Compositions Of Irregular Mare Patches (Imps) Using Remote Observations, Nicholas G. Piskurich

Graduate Thesis and Dissertation 2023-2024

Compositional characterization of lunar surface features informs our understanding of the Moon's thermal and magmatic evolution. We investigated the compositions of hypothesized volcanic features known as irregular mare patches (IMPs) and their surroundings to constrain formation mechanisms. We used six datasets to assess the composition of 12 IMPs: 1) Moon Mineralogy Mapper (M3) derived spectral parameters (e.g., band center positions, shapes), 2) Lunar Reconnaissance Orbiter (LRO) Diviner Radiometer Experiment (Diviner) measured Christiansen feature (CF) position, 3) SELENE (Kaguya) Multiband Imager (MI) FeO abundance, 4) Clementine 5-band (Ultraviolet/Visible)-derived FeO abundance, 5) LRO Wide Angle Camera (WAC) TiO2 abundance, …

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